Method and apparatus for automated trading of equity securities using a real time data analysis

ABSTRACT

A system and method for buying and selling securities based on volatility and liquidity rather than other fundamentals is demonstrated. The method involves: providing at least one decision model to buy and sell a security; inputting real-time data into the decision model; and automatically generating an order and executing transactions to buy and sell the security based in response to the decision model. The method continues in buying and selling the security based in response to decision model until the method is stopped.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of prior application Ser. No.12/098,828, filed on Apr. 7, 2008, now U.S. Pat. No. 7,552,085, which isa continuation of Ser. No. 09/500,624, filed on Feb. 9, 2000, now U.S.Pat. No. 7,356,499. The disclosure of the prior applications areincorporated herein by reference.

TECHNICAL FIELD

The present invention relates generally to automated systems for tradingsecurities, and more specifically to an apparatus and method forautomatically buying and selling equity securities based on markettrends in response to pre-established decision models for the particularsecurity.

BACKGROUND

A group of investors called day traders typically trade securitiesthroughout the trading day. Day trading may be a hobby or rise to thelevel of a career. Unlike long term investors, day traders seek tocapitalize on incremental trends in the price of securities throughoutthe trading day.

Day trading involves careful monitoring of a security and decidingwhether to buy or sell based on intraday movements of the price and thetrend of the security. Successful day trading depends on the ability torecognize a trend and the market momentum therein, timely execution of abuy or sell order, and a determination of when to forego a transaction.

There are different methods of day trading. One popular method is totrack and trade highly volatile securities by attempting to buy when thesecurity price is moving up or sell short when the security price ismoving down. Various other sources of information besides price, such asvolume, are often considered in deciding to enter into a transaction.Technical analysis of stock prices tell us that prices tend to move intrends, volume of traded securities corresponds with the trends, and atrend once established has momentum and tends to continue in force.

Some of the data that day traders monitor in order to determine a trendinclude: price; bids; asks; spread between the inside bid/ask; and thenumber of shares on the bid or ask side. Other general market data mayalso be considered such as futures contracts, economic indicators andfinancial news sources such as CNBC.

Day traders tend to focus on a very small number of stocks relative tothe entire stock market. Day traders commonly monitor real-time datapresented on the trader's computer screen. One difficulty in day tradingis analyzing the large volumes of available data. Timely decidingwhether to enter into a transaction is critical. Delays of a few secondscan make the difference in catching a trend near the start, middle orend.

Another problem with day trading is the ability to enter appropriatebuy/sell orders quickly and to have them executed. That is, once adecision is made, the order should be placed before the marketfluctuates much. Many day traders monitor multiple data sources thenmust format an appropriate buy or sell order. Particularly if multipleevents occur, a significant amount of time may lapse.

Another method of day trading is to monitor a specific stock thatusually makes little movement in price during the trading day. A daytrader may attempt to exploit a spread between a prevailing bid and askto make a small profit. This method requires repeatedly buying andselling the security. The profits are typically on the order of 1/16 or⅛ of a point. Stopping losses by quickly exiting a transaction that isnot profitable is crucial. This method of trading is commonly referredto as scalping.

Various known systems for automatic transactions have been proposed inthe prior art. Some systems are intended to create an automated marketfor securities. Two such systems are disclosed in U.S. Pat. Nos.5,950,176 and 4,674,044. These systems automate a security market bytaking buy and sell orders from several sources and setting a pricebased on supply and demand.

Other systems are intended to manage large investor portfolios or foruse by institutional investors. For example, U.S. Pat. No. 5,101,353 andother patents are commonly used for large institutional investors. Suchsystems allow institutions to anonymously buy and sell large blocks ofsecurities. The system is somewhat automated in that buy and sell ordersat specific prices are communicated to the markets where they areexecuted. However, the analyzing of the price and the determination oforders is operated by a registered investment advisor. The system isused to match internal buy and sell orders before placing market orders.

Other known systems are used in a similar fashion. That is, buy and sellorders are manually placed. Thus, the systems are only partiallyautomated. Further, many of these systems are particularly suited forinstitutional trading.

Institutional investors, retail brokerage houses and privatecorporations may also participate in program trading. Program trading asdefined by the New York Stock Exchange® (“NYSE”) involves thesimultaneous buying and selling of at least 15 different stocks with amarket value of $1,000,000 or more. Program trading is designed to takeadvantage of the inefficiencies in the market between stock prices andfutures or options contracts. Program trading is typically just pricebased. The bulk trading of stocks or options are executed at differenttimes under strict market rules. These types of systems are inherentlydifferent and not available to day traders.

It would therefore be desirable to provide a system available to daytraders that is capable of quickly entering into buy and selltransactions to take advantage of market momentum.

SUMMARY OF THE INVENTION

It is therefore one object of the invention to automatically buy, sellor sell short equity securities. It is a further object of the inventionto quickly identify and react to trends or momentum in price movementfor a security. Another object of the invention is to provide a systemthat both buys securities on the identification of a trend and sellssecurities automatically when the end of the trend is determined.

The present invention provides a method for buying and sellingsecurities based on volatility and liquidity rather than commonly usedstock fundamentals. In one aspect of the invention, a method for tradinga security comprises the steps: formulating a decision model for thesecurity; monitoring real-time market data; in response to the marketdata for the security and the decision model, automatically generating atransaction order; and transmitting the transaction order to a marketcomputer.

One feature of the invention is that it allows the system operator todevelop decision models. The decision models are not limited tovariations of traditional technical analysis but instead can includenovel analysis of data.

Another feature of the invention is that after an order is placed, thetransaction may be monitored until execution. Until the transaction hasbeen executed the decision model is monitored to determine whether tocancel the order.

A further feature is related to how a transaction is reversed onceinitiated. For example if a security is bought it can be sold through adecision model to sell or through a floating stop loss process.

In a further aspect of the invention, an automated securities tradingsystem comprises a computer for formulating a decision model for thesecurity. The computer is coupled to a network and receives real-timemarket data. The computer automatically generates a transaction order inresponse to the market data based upon the decision model. The computerplaces the order.

One advantage of the invention is that if the system is used to monitormultiple securities, different decision models may be used for each.Another advantage of the invention is that both buy and sell orders maybe automatically executed by the system so that the orders are processedquickly to take advantage of price trends and momentum in the market asdesired by day traders.

A further feature and advantage of the invention is that it may monitorreal-time data and make decisions to buy or sell on a moment by momentbasis. Several securities may be concurrently monitored through thedecision models and transacted on a moment by moment basis.

Other objects and features of the present invention will become apparentwhen viewed in light of the detailed description of the preferredembodiment when taken in conjunction with the attached drawings andappended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will become more fully understood from thedetailed description and the accompanying drawings, wherein:

FIG. 1 is a block diagrammatic view of a trading system according to thepresent invention.

FIG. 2 is a high level system flow chart according to the presentinvention.

FIG. 3 is a block diagram of data entry for the system according to thepresent invention.

FIG. 4 is a flow chart for data input validation according to thepresent invention.

FIG. 5 is a data and analysis decision flow chart according to thepresent invention.

FIG. 6 is a decision point flow chart according to the presentinvention.

FIG. 7 is a transaction portion of a flow chart.

FIG. 8 is an order preparation flow chart according to the presentinvention.

FIG. 9 is an order execution preference chart according to the presentinvention.

FIG. 10 is a floating stop loss flow chart according to the presentinvention.

FIG. 11 is a block diagrammatic view of an alternative embodiment of atrading system suitable for an on-line brokerage system.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

In the following figures like reference numerals are used to identifyidentical components in the various views. The following example ismeant to be illustrative of a preferred method for implementing theautomated trading securities system. However, those skilled in the artwill recognize various alternative embodiments. For example, variousdecision models using various security or market data may beimplemented.

Referring now to FIG. 1, an automated securities trading system 10 isillustrated. The automated trading system 10 has a personal computer(PC) 12 that is coupled to a network 14. Network 14 is coupled to a datasource computer 16 and a market computer 18. The automated tradingsystem 10 may also be remotely accessed through the network 14 byanother computer including a PC, hand held computer or a laptop computer20.

Personal computer 12 is the most likely implementation of the presentinvention. However, other computing systems such as mainframes orminicomputers may also be used.

Personal computer 12 has a central processing unit (CPU) 24 with memory26. Memory 26 includes: random access memory (RAM); read only memory(ROM); flash or cache memory; a hard drive; and other data storagedevices. Various data and a program for operating the present inventionmay reside in memory 26. CPU 24 has an interface 28 that is used tocouple personal computer 12 to network 14. Various operating systemsknown to those skilled in the art may be used to operate personalcomputer 12. CPU 24 operates the software in conjunction with inputdevices such as a keyboard 30 and a mouse 32. Various data are displayedon a monitor 34. A printer 36 coupled to computer 12 is used to printdisplayed information and reports, from computer 12.

Network 14 is illustrated as hard wire connections between computer 12,data source 16 and market computer 18. Network 14 may, for example, bethe Internet, or other network known to those skilled in the art.Interface 28 represents the connection to the network 14. Interface 28may include but is not limited to a dial up modem, a cable modem, anISDN line, a DSL line, a T1 line, or various other data lines andconnectors known to those skilled in the art. Interface 28 may alsoinclude but is not limited to: wireless connections such as throughsatellites; high data rate wireless technology (HDR); or wireless phonenetworks.

Although illustrated as a single wide area network (WAN), the presentinvention may be implemented using several networks including a localarea network (LAN). For example, both a WAN and a LAN may be used. For aLAN, a client/server network may be used having various numbers ofclient workstations connected thereto. The client/server network may becoupled to a WAN such as the Internet.

Data source 16 is illustrated as a single source. However, data source16 represents a variety of potential data sources. Computer 12 may beused to select desired information from the variety of data sources.Data source 16 preferably provides real-time security data. Although,this real-time security data may also be provided together withhistorical data. Data source 16 specifically may provide NationalAssociation of Securities Dealers Automated Quotation System (“NASDAQ”)level II data or similar data. NASDAQ level II data provides detailedinformation about the current market for a specific security. Level IIdata includes details about bids, and asks, as well as the identity ofthe market maker for the bid/ask and numbers of shares offered. Also,the numbers of shares and the time that they were sold is also provided.

Sources for data such as NASDAQ level II are available through severalthird-party vendors including: Bridge; S & P Comstock; and, eSignal.Data source 16 may include but is not limited to any of the abovesources.

The present invention is intended to work with various types of marketcomputers 18. For example, the present invention preferably isconfigured to allow communication with the NYSE, NASDAQ, and variouselectronic communication networks (ECN) such as ISLAND. Market computer18 may be an Internet brokerage as well. Market computer 18 acceptspreformatted security orders and implements the transaction as soon asthe market will accept it. A confirmation is provided by market computer18 upon the actual transaction being completed. A preferred embodimentof the market computer will allow for direct access electronic trading(DAET).

Data source 16 and market computer 18 may coexist at a common location.For example, data source 16 and market computer 18 may exist together atan Internet brokerage. Data source 16 and market computer 18 may also beintegral meaning they exist as one computer system, for example theNASDAQ computer system or the NYSE computer system. Alternatively, datasource 16 and market computer 18 may exist at different locations and beaccessed by different means. For example, interface 28 for the datasource 16 may be a satellite connection. At the same time interface 28for the exchange computer 18 may be an Internet connection through atelephone modem.

Referring now to FIG. 2, a high-level flow chart of the operation of thepresent invention is illustrated. In block 40, data for selected stocksare input and analyzed. The identity of securities to transact andassociated decision models are taken from database 42 and stored inmemory 26 for processing in step 40 by computer 12. Block 44 provides asource for real-time stock data. The data may be obtained from datasource 16. Real-time data from block 44 may eventually become part ofhistorical databases 42 for use in decision models.

In block 46 orders are prepared and submitted. The orders may includebuy orders, sell orders, sell short and buy to cover orders. Theseorders are prepared in response to the real-time data for selectedstocks from step 40 and based upon the formulated decision modelstherein. These transactions are prepared and formatted in CPU 24. Theorders are transmitted to a brokerage or directly to an exchange 48. Inresponse to executed orders, a transaction database 50 may be used tostore historical data for transactions of the system.

Referring now to FIG. 3, to initialize the system, a database ofsecurity data 51 and a system database 52 is constructed. Computer 12 inblock 54 prompts the user for security symbols to monitor as well asvarious information about each security. The prompted information willgenerate the decision model for the various securities. Examples ofinformation to be input in block 54 include: the number of levels ofdecision; the relationship of levels; the components and databases; therelationship between components; various equations; decision points; thenumber of shares to buy or limits therein; the holding period; variouscircuit breakers; exchange preferences; and, any additional data deemedsignificant in the operation of the system. As part of this processvarious databases 56, 58, and 60 can be established to receive and storesecurity data to be used in components. Once a decision model isestablished it can be applied to any security. The system will offer theoperator the option of selecting or modifying decision models providedwith the system. Each area of additional information is discussed ingreater detail below.

1. Number of Levels of Decision

A “level” refers to a separate grouping of components in the decisionprocess. There must be at least one level and there may be several butin most applications only a few will be appropriate. The user enters anumber of levels of decision from 1 to n.

For example one level may be selected with two components therein.Alternatively, four levels can be used with the first two using a singlecomponent and the next two using three and four components respectively.Nearly an unlimited number of combinations are available.

In the decision process a level will return a true or false value. Alevel returns a true or false value depending on whether the componentshave reached their decision points or range.

2. Relationship of the Levels

The relationship between levels is a decision process as it relates tothe levels. In general, a Boolean operation such as AND, OR, NOT will beused to compare the levels for making a decision. For example a decisionmodel could have two levels with the following relationship: Level 1<AND> Level 2. An alternative model could employ three levels with thefollowing relationship: (Level 1 <OR> Level 2) <NOT> Level 3. The userwill have virtually unlimited discretion in the relationship of levels.

3. Components and Databases

A “component” can be an element of data or an assigned function of datafor a security, or market in general. With few exceptions the securitydata of interest is dynamic and available in real-time. Security dataincludes but is not limited to its: price; volume; bids; asks; spread;number of shares at each price level of bid; number of shares at eachprice level of ask; time and sales; actions of market makers orspecialists. Market data includes but is not limited to the following:NASDAQ volume or level; S&P futures volume or level; and Dow volume orlevel. There can be more than one function of a certain data type.

For example, a component may be a function of volume traded for asecurity. Another component could be a function of how close the currentprice is to the inside bid or ask. A third component may be a functionof the S&P futures. A fourth component may be based on tracking theactivities of market makers. One of several ways this may be done is toassign a value to each of the finite number of market makers. Acomponent may then be developed to track the activities of market makersincluding their offers or bids. The group of components available isonly limited by the data accessible for a specific security or market.

A component can also be a function of historical data retrieved from adatabase for a security. Component databases 56, 58, 60 illustrate thedatabases that can be established for creating a source for componentdata. To create a component database, the user defines the data orfunction of data that is placed in the database. Any of the availablesecurity data that can be incorporated into a component may be placed ina component database. For example, a component could relate to thevolume of shares traded and number of trades made at a specific pricelevel. This type of component database may be used to identify supportand resistance levels. A component may then be established to anticipatebuying or selling pressure based on the database for how actively thesecurity was traded in the past as the security approached a certainprice level.

As illustrated, several component databases 58, 59 and 60 can beestablished for each level in the decision model. A virtually unlimitednumber of component databases can be established for each separatedecision model.

In a preferred embodiment, a selection from an offering of the mostcommonly used components and component databases may be offered. Othercomponents or functions of data may be customized.

4. Relationship of Components

There are several ways of defining a relationship between the componentson each level. These include but are not limited to the following: 1.weighted data summation; 2. interaction or intersection; and, 3.singular values.

Each level can combine more than one component. In the intersection orinteraction relationship the components may have a relationship thatallows them to be combined to produce a net result. For example, onecomponent may be a moving average of price for the preceding thirtyticks of data. Another component may be a moving average of price forthe preceding ten ticks. A relationship may then be established where ifone moving average crosses the other, then the condition (buy, sell,etc.) for the level has been met.

In the weighted data format the components are assigned equations thatgives weight to the data. For example, one level could have threecomponents. The first component may be a measure of volume. The secondcomponent may be a measure of price change. The third component may be ameasure of how close the price is to the inside bid or ask. Arelationship may then be established where the volume component is 20%of the total, the measure of price change may be 30% of the total, andthe spread 50% of the total. This means no matter how high the volumegoes it can only contribute 20% to the total deciding factor.

A significant value of this method is that it allows a combining of datathat does not easily lend itself to comparison. It also allows forcreating a sliding scale for each component that when combined producesa sliding scale of the total where no one component exclusively controlsthe net result.

5. Equations or Formulas

Each component may be assigned an equation that works as a function ofsecurity data. The assigned equation serves more than one purpose.First, the equation may be a function of the data that gives it meaning.Second, the equation in the weighted data relationship may establish acontinuum between low and high values. Third, in the weighted dataformat it may be used to give a weight to the data that can then becombined with other weighted data to give a combined result.

The user may be given options of equations for a component as part ofthe component selection process. Alternatively, a customized equationmay be entered.

6. Decision Points

A decision point refers to the moment data entered into a componentreaches a predetermined level that satisfies the users criteria, in thatcomponent, for making the decision to buy, sell, sell short or buy tocover. A decision point may be a number, range of numbers or interactionbetween functions. For example a decision point may be when the price ofa security increases by ⅛ point. It may also be when the average volumefalls within a certain range. In addition a decision point could be whentwo different trailing averages intersect. The user has wide discretionin the definition of decision points.

As illustrated in block 62 information will be requested for input tosystem database 52. Block 62 may prompt the user for various pieces ofdata with respect to the overall system. For example, block 62 mayprompt the user for system circuit breaker, brokerage and accountinformation, the access method to the brokerage or to the exchange, theaccess method to the real-time data for securities, and any other systeminformation.

Other information about the total number of shares that the systemshould buy or sell short may be used. It also tells the system how manyshares should be bought or sold in a single transaction.

In block 54 information about holding periods, circuit breakers,exchange preferences and additional data will also be requested. Holdingperiod refers to issues such as whether to hold a security overnight orhave a mandatory sell at the end of the day.

Circuit breakers refer generally to trigger points that require a haltin part or all trading. An example may be when the system executes toomany trades in a given time period. Another example of a circuit breakeris when the system achieves a level of draw down (loss of capital) thatis not acceptable. Several circuit breakers may be offered.

Exchange preferences refer to user defined preferences for theparticular exchange to use and the type of order to execute. For exampleall trading could be limited to one ECN such as ISLAND or spread aroundto several. In addition the order to buy could be always at the marketor at the inside bid. Several options will be available.

As illustrated in block 62 there are several areas of informationrequested including: system circuit breakers; brokerage and accountinformation; access method to brokerage; access method to real-timedata; and, additional information.

System circuit breakers apply similar types of consideration as thecircuit breakers for specific securities as discussed above. An examplecould be the maximum amount of draw down for the system including allsecurities being traded. Another example of a circuit breaker may be anevent such as the markets shutting down. Several circuit breakers willbe offered.

Information about brokerage, account and access to data will tell thesystem the parameters it must work under for buying and sellingsecurities and accessing data.

Referring now to FIG. 4, a flow chart of the system is illustratedcontinuing through FIG. 8. Step 418 requests the securities data andmarket data to be monitored. The securities to request data for areidentified in the security database 419 (as input in step 54). The datais requested from a data source in step 420. This is the same source asdata source computer 16 of FIG. 1. The security and market data fromstep 420 is raw data as illustrated in step 421. The raw data iscompared to historical data in step 422 to verify that the data is in avalid range. If the data is outside of a valid range, then the samesecurity data is requested again in step 420.

If the data is valid, the process continues in FIG. 5 at step 523, wheredata is entered in the component equations and databases. Step 523 willreceive the identity of component equations and component databases forthe corresponding securities to be traded from database 524. Dataentered may also be saved in a component database in step 525. The flowof data into decision models and component databases is continuous.

Step 526 illustrates the process of calculating the results of the datain the components of the decision models and comparing the results todecision points as will be further discussed below.

As a result of step 526 a decision may be made to buy, sell, sell shortor buy to cover a security. This is illustrated in steps 527, 528, 529,530. The decision to buy, for example, is available for a specificsecurity if the user selected that option and selected a buy decisionmodel for the security. If a buy, sell, sell short or buy to cover orderis not appropriate pursuant to a decision model then the systemcontinues to monitor the decision models in process 526. The system willcontinue processing data through the input and decision models until thesystem is halted by the operator or by other system parameters.

If a decision is made to buy, sell, sell short or buy to cover then thesystem will proceed to step 531 where additional considerations aretaken into account before a transaction is entered into. The embodimentof the process in step 531 is discussed in greater detail in FIG. 7below. This step looks at whether to proceed based on several factors.

Step 531 checks to determine whether or not the transaction isappropriate. Information from a database 532 of security data includingtransaction limits, exchange and order preferences may be used in thisprocess. Usually these parameters are input to the database prior toentering automatic transaction mode. In step 533, the appropriateness ofthe transaction is determined. If the transaction is not appropriate theprocess is returned to step 526. If the transaction is determined asappropriate, step 534 is executed.

Step 534 determines the best order type and which exchange to be used.For example, an order may be placed on more than one exchange. In step535, the order is sent to the appropriate exchange or exchanges and anentry is made in the transaction database in step 536. In step 537, thesystem determines whether or not timely confirmation has been received.If no confirmation has been received, then step 538 may be executedwherein orders are resubmitted and checked for errors. After step 538,step 535 resubmits the order to the exchange or cancels the order ifnecessary. Referring back to step 534, during the ordering process, thesystem process flow may simultaneously return back to step 526 and sendthe order to the exchange in step 535. This allows the furtherprocessing of the decision models while the order is being processed.Back in step 526, if the decision points or ranges have not been reachedthen an order may be cancelled if it has not been executed.

Referring now to FIG. 6, the logic of step 526 is illustrated in moredetail. FIG. 6 provides one example of a decision model for a buydecision. A similar example applies to a decision model for a selldecision, sell short decision, or a buy to cover decision. FIG. 6 is oneexample of countless variations of a decision model. Step 638illustrates Level 1 of the decision model. As discussed in reference toFIG. 3 there can be one or several levels in the decision model. Steps639 and 640 illustrate the possible addition of Level 2 and Level 3.Step 638 illustrates a weighted data summation format for the componentsin Level 1. This is but one of the several options for defining therelationship between the components for Level 1.

As illustrated in step 638, for Level 1 to be TRUE requires that the sumof the weighted data be greater than or equal to its decision level. Anexample of process 638 is as follows:

If Σƒ(Comp_(—)1) to ƒ(Comp_n)≧DPoint1 then Level 1 is TRUE

In this example ƒ(Comp_(—)1) represents a function of security data forComponent 1. Additional functions of security data for components arerepresented by ƒ(Comp_n). The decision point for Level 1 is representedby the variable DPoint1.

As illustrated in process 639, for Level 2 to be TRUE requires thatthere be intersection or interaction between the components. An exampleof process 639 is as follows:

If ƒ(Comp_(—)1)≧ƒ(Comp_(—)2) then Level 2 is TRUE

In this example the functions of Component 1 and Component 2 arecompared. One example may be when moving average of data is compared toanother moving average.

As illustrated in process 640, for Level 3 to be TRUE requires that acomponent reach a specific value. An example of process 640 is asfollows:

If ƒ(Comp_(—)1)=DPoint3 then Level 3 is TRUE

The above examples are illustrative of the different types ofrelationships available for each level of a decision model. There areunlimited variations as to the number of Levels in a decision model andthe number and type of components at each level. The above exampleillustrates one of many options available.

Step 641 represents the final step of the decision model where theresults of the separate levels are combined in an IF . . . THEN Booleanlogic type operation. If the result of operation 641 is true then thesystem will proceed to step 527 where the system will proceed to prepareand submit a buy order for the security. For example, if there are threelevels and the relationship in step 641 is represented as Level 1 <AND>Level 2 <NOT> Level 3 then for a buy decision to be made requires thatboth Level 1 and Level 2 have reached their decision point and Level 3has not reached its decision point. If this occurs then the decisionmodel will reach a buy decision.

Referring now to FIG. 7, the logic that determines the appropriatenessof a transaction for steps 531 and 533 is illustrated. FIG. 7illustrates the logic in the event of a buy decision as a result ofprocess 526. Similar logic would apply in the event of a sell decision,sell short decision, and buy to cover decision. In step 742, if thesecurity is already owned and the total to buy is not yet reached, thenstep 743 is executed. If the maximum number of transactions has not beenreached, then step 744 is executed. If an operator defined level of drawdown has not been reached, step 745 is executed if appropriate. Inoptional step 745, additional conditions may be required to be met todetermine whether or not the transaction is appropriate. If all of theabove are true, then step 533 indicates an appropriate transaction isreached. If in steps 742 through 745 the logic is no, then a transactionwill not be entered for the particular security.

Referring now to FIG. 8, the process for determining the best type oftransaction from steps 535 is illustrated. In step 846, the best stockexchange is determined based on user preferences and the liquidity ofthe exchange for the security is determined. For example, one ECN may bedesirable over another due to transaction costs or offering a better bidprice. In step 847, the best method for order execution or as modifiedby user preferences may be determined. Step 847 looks to the pricemomentum, availability of shares and activities of market makers indetermining the best method for order execution. In addition, step 847will formulate an order that complies with established order rules forthe exchange and order type to be used. Part of the information forsteps 846 and 847 may be input from a database of security data thatincludes the preferences as pre-defined.

Referring now to FIG. 9, an example of the logic in step 847 above thatmay apply to determining the type of order based on order type and pricemomentum. A chart illustrates various market momentums and buy, sell orsell short orders. Various order types include: bid which is either highor low; an offer which can be either high or low; a small orderexecution system (SOES) order; and, a preference order to a specificmarket maker. An example of a determination of what type of order to beexecuted is illustrated. For example, for a buy order, depending on themarket momentum, that is a momentum increasing, decreasing or stayingthe same, a bid may be processed high or low, respectively. A preferenceto a specific market maker may be bid high. If the momentum isdecreasing, a bid between the spread may be formed and if the momentumis flat a bid between the spread may be formed. Also, if the momentum isincreasing or staying the same, a SOES order may be placed.

If a sell order is required and the momentum is increasing, decreasingor staying the same, an offer high, an offer low, or an offer high maybe formed respectively. Alternatively, an offer between the spread, anoffer preference low, or an offer between the spread may be formed.Also, a SOES order may be implemented if the momentum is decreasing orstaying flat.

If a sell short order is determined and the momentum is increasing,decreasing or staying the same, an offer high or an SOES order on anuptick may be performed. Alternatively, an offer between the spread andan offer low on an uptick may be generated. If the price momentum isfalling or flat an offer at a predetermined level above the currentprice may be offered on a downtick. For example, an offer of 1/16 abovethe price may be executed.

Referring now to FIG. 10, a floating stop loss may also be used todetermine when to sell or buy to cover a particular security. Thefloating stop loss illustrated in FIG. 10 is different from that of atraditional stop loss. A floating stop loss is a feature of the instantinvention's constant monitoring of the market for the security. Ratherthan the traditional method where a stop loss order for a specificamount is sent to the broker, a floating stop loss is accomplished whenthe system determines to exit the transaction and immediately sends anorder for execution. Another distinct advantage of the floating stoploss is that it can follow the advance of a security and exit at themoment the stock turns down. A trading method can be developed where asecurity is bought according to a buy decision model and sold based onthe floating stop loss rather than a sell model.

Step 1049 illustrates the basic concept of the floating stop loss whenthe security is owned. HPrice is a variable for the highest price forthe security from the time of its purchase. CPrice is a variable for thesecurity current price. BStop is a variable for the stop loss amountthat the current price can differ from the highest price beforerequiring a sell order. In a floating stop loss BStop can be fixed at anamount such as 1/16th point and ¼th point. In a dynamic floating stoploss BStop may be set to increase or decrease based on the continuedincrease in the security price. For example, BStop can be set toincrease 1/16th point for every point increase in price.

Step 1050 illustrates a floating stop loss for a security sold short. Inthis step LPrice is a variable for the lowest price for the securityfrom the time that it was sold short. CPrice is a variable for thesecurity current price. SStop is the variable for the stop loss amount.As in step 1049, SStop can be fixed at a specific amount for a floatingstop loss or variable as the price decreases for a dynamic floating stoploss.

In step 1049 or step 1050 if the logic is no, step 1051 is executed. Instep 1051, if there is no other reason to reverse the transaction thenthe logic loops back to step 1049 or step 1050 for further checking.Concurrent or parallel to this process the decision models continue tobe monitored to determine if they dictate a reversal of the transaction.In step 1049 or step 1050 if the logic is yes, then step 534 isperformed.

Referring now to FIG. 11, an embodiment of the invention is illustrated.The present embodiment is suitable as an option for traders using acommon source such as an Internet brokerage 1105. Internet brokerage1105 has as resident on its computers' programs to implement the methodsof the instant invention. Internet brokerage 1105 receives its marketdata from data source computers 1101 and connects to market computers1103. Computers 1101 and 1103 may be implemented on the same computersystem and may be integral. For example, computers 1101 and 1103 may bethe common computer system of NASDAQ computers. Internet brokerage 1105may include one or more mainframe computers or minicomputers withassorted microcomputers connected.

Servers 1107, 1109, 1111 represent a plurality of servers on theInternet connecting the Internet brokerage 1105 to the client computers1113, 1115, 1117, 1119, 1121, and 1123. Client computers 1113, 1115,1117, 1119, 1121, and 1123 may be of the type as described above. Theclient computers may also be “dumb” terminals such as a WebTV® device.Through their client computers the system users will be able toestablish the parameters of the trading as discussed above. However, inthis embodiment most, if not all, of the processing of the decisionmodels may take place at the Internet brokerage computers 1105.Information about transactions will be displayed at the clientcomputers. One advantage to such a system is that because trades areautomatically executed, one less link, i.e., to the end user and back,during execution is performed. Therefore, any time associated with thatconnection is eliminated when executing a trade. Because market momentummay be rapid, timely execution of trades may reduce cost and increasethe overall profits of the transaction.

In operation, a predetermined number of securities are identified to thesystem. A decision model for each of the securities is determined.Real-time market data is monitored as well as information from thedatabases. In response to the market data for the security and thedecision model, a transaction order is automatically generated. Thesystem automatically transmits the transaction order to the marketcomputer. During the process and before execution of the order, theorder is continually monitored to determine if it is appropriate. If thetransaction at any time before execution is determined to beinappropriate, the order may be canceled. In addition, the system may berun in a training mode allowing the decision models to be tested priorto actual implementation and actual trading.

While particular embodiments of the invention have been shown anddescribed, numerous variations and alternate embodiments will occur tothose skilled in the art. Accordingly, it is intended that the inventionbe limited only in terms of the appended claims.

1. A computer implemented method for automated and repeated buying andselling a security through a first computer system in communication witha market computer system, the method comprising: providing an ability toselect a buy decision model and a sell decision model for trading asecurity wherein the buy decision model decides at least in part whetherto buy the security and the sell decision model decides at least in partwhether to sell the security wherein the buy decision model comprises amathematical expression for receiving data and providing at least onevalue wherein the mathematical expression comprises at least onemathematical operator and at least one variable wherein the mathematicaloperator is at least one of a multiplication operator, a divisionoperator, and an addition operator; inputting, by the first computersystem, the data into a selected buy decision model wherein the datacomprises continually changing real time security data wherein the datais continually inputted into the buy decision model; resolving, by thefirst computer system, the mathematical expression of the selected buydecision model and comparing, by the first computer system, the resultto a decision point wherein the decision point comprises one of a secondmathematical expression, a value and a range of values; when theselected buy decision model indicates a decision to buy the securitybased at least in part upon comparing, by the first computer system, theresult to the decision point, then automatically generating a buytransaction order for the security and automatically transmitting thebuy transaction order to the market computer system, otherwise returningto the above step of resolving, by the first computer system, themathematical expression of the selected buy decision model; monitoring,by the first computer system, a selected sell decision model for adecision to sell the security; when the selected sell decision modelindicates a decision to sell the security then automatically generatinga sell transaction order for the security and automatically transmittingthe sell transaction order to the market computer system, otherwisereturning to the above step of monitoring, by the first computer system,the selected sell decision model; and repeating the above stepsbeginning with the step of resolving, by the first computer system, themathematical expression of the selected buy decision model, by thecomputer.
 2. The computer implemented method for automated and repeatedbuying and selling a security through a first computer system incommunication with a market computer system of claim 1, furthercomprising: providing for modifying the buy decision model.
 3. Thecomputer implemented method for automated and repeated buying andselling a security through a first computer system in communication witha market computer system of claim 1, wherein the mathematical expressionis a moving average of the real time security data.
 4. The computerimplemented method for automated and repeated buying and selling asecurity through a first computer system in communication with a marketcomputer system of claim 1, wherein the buy decision model furthercomprises a Boolean expression wherein comparing the result to thedecision point returns a true or false indicator wherein a trueindicator indicates a decision to buy the security.
 5. The computerimplemented method for automated and repeated buying and selling asecurity through a first computer system in communication with a marketcomputer system of claim 1, further comprising: providing for modifyingthe buy decision model wherein one or more additional variables areincluded in the decision model.
 6. The computer implemented method forautomated and repeated buying and selling a security through a firstcomputer system in communication with a market computer system of claim1, wherein the buy decision model comprises a database variable whereinthe database variable receives historical data from a database apartfrom the real time security data.
 7. The computer implemented method forautomated and repeated buying and selling a security through a firstcomputer system in communication with a market computer system of claim6, wherein the database comprises historical data for the security. 8.The computer implemented method for automated and repeated buying andselling a security through a first computer system in communication witha market computer system of claim 1, further comprising: providing formodifying the buy decision model wherein one or more additionalvariables are included in the decision model wherein the decision modelcomprises a Boolean expression and wherein the step of resolving, by thefirst computer system, the mathematical expression and comparing, by thefirst computer system, the result to a decision point further comprisesusing an inequality sign for comparing the result to the decision pointwherein the inequality sign comprises one of a greater-than sign, aless-than sign, a greater-than or equal-to sign and a less-than orequal-to sign and wherein the result is a true or false indicationwherein a true indication is a decision to buy the security.
 9. Thecomputer implemented method for automated and repeated buying andselling a security through a first computer system in communication witha market computer system of claim 1, wherein the sell decision modelcomprises a mathematical expression for receiving data and providing, atleast one value wherein the mathematical expression comprises at leastone mathematical operator and at least one variable wherein themathematical operator is at least one of a multiplication operator, adivision operator, and an addition operator.
 10. The computerimplemented method for automated and repeated buying and selling asecurity through a first computer system in communication with a marketcomputer system of claim 1, wherein the buy decision model comprises amoving average and the decision point comprises a second moving average.11. The computer implemented method for automated and repeated buyingand selling a security through a first computer system in communicationwith a market computer system of claim 1, wherein the data comprisesmore than price data for the security.
 12. The computer implementedmethod for automated and repeated buying and selling a security througha first computer system in communication with a market computer systemof claim 1, wherein the data comprises price data for the security andvolume data for the security.
 13. The computer implemented method forautomated and repeated buying and selling a security through a firstcomputer system in communication with a market computer system of claim1, wherein the step of resolving, by the first computer system, themathematical expression and comparing the result to a decision point,further comprises: using an inequality sign for comparing the result tothe decision point wherein the inequality sign comprises one of agreater-than sign, a less-than sign, a greater-than or equal-to sign anda less-than or equal-to sign.
 14. A computer implemented method forautomated and repeated buying and selling a security through a firstcomputer system in communication with a market computer system, themethod comprising: providing an ability to select a decision model fortrading a security wherein the decision model comprises a buy decisionlogic for deciding at least in part whether to buy the security and asell decision logic for deciding at least in part whether to sell thesecurity wherein the buy decision logic comprises a mathematicalexpression for receiving data and providing at least one value whereinthe mathematical expression comprises at least one mathematical operatorand at least one variable wherein the mathematical operator is at leastone of a multiplication operator, a division operator, and an additionoperator; computer implemented inputting, by the first computer system,the data into a selected decision model wherein the data comprisescontinually changing real time security data wherein the data iscontinually inputted into the decision model; resolving, by the firstcomputer system, the mathematical expression of the selected decisionmodel and comparing the result to a decision point wherein the decisionpoint comprises one of a second mathematical expression, a value and arange of values; when the selected decision model indicates a decisionto buy the security based at least in part upon comparing, by the firstcomputer system, the result to the decision point, then automaticallygenerating a buy transaction order for the security and automaticallytransmitting the buy transaction order to the market computer system,otherwise returning to the above step of resolving, by the firstcomputer system, the mathematical expression of the selected decisionmodel; monitoring, by the first computer system, the selected decisionmodel for a decision to sell the security; when the selected decisionmodel indicates a decision to sell the security then automaticallygenerating a sell transaction order for the security and automaticallytransmitting the sell transaction order to the market computer system,otherwise continuing monitoring the selected decision model; andrepeating the above steps beginning with the step of resolving, by thefirst computer system, the mathematical expression of the selecteddecision model.
 15. The computer implemented method for automated andrepeated buying and selling a security through a first computer systemin communication with a market computer system of claim 14, furthercomprising: providing for modifying the decision model.
 16. The computerimplemented method for automated and repeated buying and selling asecurity through a first computer system in communication with a marketcomputer system of claim 14, wherein the mathematical expression is amoving average of the real time security data.
 17. The computerimplemented method for automated and repeated buying and selling asecurity through a first computer system in communication with a marketcomputer system of claim 14, wherein the decision model furthercomprises a Boolean expression.
 18. The computer implemented method forautomated and repeated buying and selling a security through a firstcomputer system in communication with a market computer system of claim14, wherein the sell decision logic comprises a mathematical expressionfor receiving data and providing at least one value wherein themathematical expression comprises at least one mathematical operator andat least one variable wherein the mathematical operator is at least oneof a multiplication operator, a division operator, and an additionoperator.
 19. The computer implemented method for automated and repeatedbuying and selling a security through a first computer system incommunication with a market computer system of claim 14, wherein theselected decision model comprises a moving average and the decisionpoint comprises a second moving average.
 20. The computer implementedmethod for automated and repeated buying and selling a security througha first computer system in communication with a market computer systemof claim 14, wherein the data comprises more than price data for thesecurity.
 21. The computer implemented method for automated and repeatedbuying and selling a security through a first computer system incommunication with a market computer system of claim 14, wherein thestep of resolving, by the first computer system, the mathematicalexpression and comparing the result to a decision point, furthercomprises: using an inequality sign for comparing the result to thedecision point wherein the inequality sign comprises one of agreater-than sign, a less-than sign, a greater-than or equal-to sign anda less-than or equal-to sign.
 22. A computer implemented method forautomated and repeated buying and selling a security through a marketcomputer system, the method comprising: providing a first computersystem in communication with the market computer system; through thefirst computer system selecting a buy decision model and a sell decisionmodel for automated and repeated buying and selling a security, by thecomputer, through the market computer system wherein the buy decisionmodel decides at least in part whether to buy the security and the selldecision model decides at least in part whether to sell the securitywherein the buy decision model comprises a mathematical expression forreceiving data and providing at least one value wherein the mathematicalexpression comprises at least one mathematical operator and at least onevariable wherein the mathematical operator is at least one of amultiplication operator, a division operator, and an addition operator;initiating computer implemented automated trading with the selected buydecision model and the selected sell decision model wherein data isinputted into the selected buy decision model and the mathematicalexpression is resolved, by the first computer system, wherein when theselected buy decision model indicates a decision to buy the securitythen a buy transaction order is automatically generated andautomatically transmitted, by the first computer system, to the marketcomputer system and when the selected sell decision model indicates adecision to sell the security then a sell transaction order isautomatically generated and automatically transmitted, by the firstcomputer system, to the market computer system, otherwise no transactionorder is generated; and continuing, by the computer, automated tradingof the preceding step until the method is stopped.
 23. The computerimplemented method for automated and repeated buying and selling asecurity through a market computer system of claim 22, furthercomprising: modifying the buy decision model.
 24. The computerimplemented method for automated and repeated buying and selling asecurity through a market computer system of claim 22, furthercomprising: selecting one or more variables for the buy decision modelwherein the one or more variables relate to at least one of securitypricing data and security volume data.
 25. The computer implementedmethod for automated and repeated buying and selling a security througha market computer system of claim 22, further comprising: modifying thebuy decision model wherein the buy decision model comprises a movingaverage of the data for the security.
 26. The computer implementedmethod for automated and repeated buying and selling a security througha market computer system of claim 22, wherein the first computer systemis a brokerage computer system in communication with a client computersystem and the market computer system wherein transactions to buy andsell the security are communicated from the brokerage computer system tothe market computer system.
 27. The computer implemented method forautomated and repeated buying and selling a security through a firstcomputer system in communication with a market computer system of claim1, wherein the first computer system is a user computer system.
 28. Thecomputer implemented method for automated and repeated buying andselling a security through a first computer system in communication witha market computer system of claim 1, wherein the first computer systemis a brokerage computer system.
 29. The computer implemented method forautomated and repeated buying and selling a security through a firstcomputer system in communication with a market computer system of claim1, wherein the first computer system comprises a user computer system incommunication with a brokerage computer system.
 30. The computerimplemented method for automated and repeated buying and selling asecurity through a first computer system in communication with a marketcomputer system of claim 1, wherein the first computer system comprisesa user computer system in communication with a brokerage computer systemwherein each step of the method is performed by at least one of the usercomputer system and the brokerage computer system.
 31. The computerimplemented method for automated and repeated buying and selling asecurity through a first computer system in communication with a marketcomputer system of claim 1, wherein the security is an equity security.32. The computer implemented method for automated and repeated buyingand selling a security through a first computer system in communicationwith a market computer system of claim 14, wherein the first computersystem is a user computer system.
 33. The computer implemented methodfor automated and repeated buying and selling a security through a firstcomputer system in communication with a market computer system of claim14, wherein the first computer system is a brokerage computer system.34. The computer implemented method for automated and repeated buyingand selling a security through a first computer system in communicationwith a market computer system of claim 14, wherein the first computersystem comprises a user computer system in communication with abrokerage computer system.
 35. The computer implemented method forautomated and repeated buying and selling a security through a firstcomputer system in communication with a market computer system of claim14, wherein the first computer system comprises a user computer systemin communication with a brokerage computer system wherein each step ofthe method is performed by at least one of the user computer system andthe brokerage computer system.
 36. The computer implemented method forautomated and repeated buying and selling a security through a marketcomputer system of claim 22, wherein the first computer system is a usercomputer system.
 37. The computer implemented method for automated andrepeated buying and selling a security through a market computer systemof claim 22, wherein the first computer system is a brokerage computersystem.
 38. The computer implemented method for automated and repeatedbuying and selling a security through a market computer system of claim22, wherein the first computer system comprises a user computer systemin communication with a brokerage computer system.
 39. The computerimplemented method for automated and repeated buying and selling asecurity through a market computer system of claim 22, wherein the firstcomputer system comprises a user computer system in communication with abrokerage computer system wherein each step of the method is performedby at least one of the user computer system and the brokerage computersystem.